Diabetes Mellitus Prediction Using Artificial Neural Network
Student: Ayomide Michael Aladetuyi (Project, 2025)
Department of Computer and Information Science
Bamidele Olumilua University of Edu. Science and Tech. Ikere Ekiti, Ekiti State
Abstract
The project addresses the global health concern of diabetes mellitus by creating a predictive model using an Artificial Neural Network (ANN). The model was trained and tested on the "Early-Stage Diabetes Risk Prediction Dataset" from Mendeley, which includes demographic and clinical symptom data. After data preprocessing and an 80-20 train-test split, the developed ANN model achieved a high accuracy of 98%. The project successfully deployed this model into a functional web application using Google Colab and Gradio, showcasing a practical tool for early diabetes risk assessment.
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For the full publication, please contact the author directly at: aladetuyiayosire@gmail.com
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Institutions
- Ekiti State University 58
- Ekiti State University, Ado-Ekiti, Ekiti State 881
- Elizade University, Ilara-Mokin, Ondo State 100
- Emmanuel Alayande College of Education, Oyo. (affl To Ekiti State Univ) 2
- Enugu State Polytechnic, Iwollo, Enugu State 4
- Enugu State University of Science and Technology, Enugu, Enugu State 29
- Evangel University, Akaeze, Ebonyi State 2
- FCT COLLEGE OF EDUCATION, ZUBA ,( AFFILIATED TO ABU, ZARIA), FCT-ABUJA 5
- Federal College of Agricultural Produce Tech, Hotoro Gra Ext, Kano, Kano State 2
- Federal College of Educ. (Special), Oyo, Oyo State (Aff To Uni. Ibadan) 10